Reliable e-nose for air toxicity monitoring by filter diagonalization method

This paper introduces a compact, affordable electronic nose (e-nose) device devoted to detect the presence of toxic compounds that could affect human health, such as carbon monoxide, combustible gas, hydrogen, methane, and smoke, among others. Such artificial olfaction device consists of an array of six metal oxide semiconductor (MOS) sensors and a computer-based information system for signal acquisition, processing, and visualization. This study further proposes the use of the filter diagonalization method (FDM) to extract the spectral contents of the signals obtained from the sensors. Preliminary results show that the prototype is functional and that the FDM approach is suitable for a later classification stage. Example deployment scenarios of the proposed e-nose include indoor facilities (buildings and warehouses), compromised air quality places (mines and sanitary landfills), public transportation, mobile robots, and wireless sensor networks.

A 15-Gbps BiCMOS XNOR gate for fast recognition of COVID-19 in binarized neural networks

The COVID-19 pandemic is spreading around the world causing more than 177 million cases and over 3.8 million deaths according to the European Centre for Disease Prevention and Control. The virus has devastating effects on economies, health, and well-being of worldwide population. Due to the high increase in daily cases, the available number of COVID-19 test kits in under-developed countries is scarce. Hence, it is vital to implement an effective screening method of patients using chest radiography since the equipment already exists. With the presence of automatic detection systems, any abnormalities in chest radiography that characterizes COVID-19 can be identified. Several artificial-intelligence algorithms have been proposed to detect the virus. However, neural networks training is considered to be time-consuming. Since computations in training neural networks are spent on floating-point multiplications, high computational power is required. Multipliers consume the most space and power among all arithmetic operators in deep neural networks. This paper proposes a 15 Gbps high-speed bipolar-complementary-metal-oxide-semiconductor (BiCMOS) exclusive-nor (XNOR) gate to replace multipliers in binarized neural networks. The proposed gate can be implemented on BiCMOS-based field-programmable gate arrays (FPGAs). This will significantly improve the response time in identifying chest abnormalities in CT scans and X-rays.

Performance Analysis of Ring Oscillators and Current-Starved VCO in 45-nm CMOS Technology

This paper presents a relative study among two Ring oscillators architecture (CMOS, NMOS) and current-starved Voltage-controlled oscillator (CS-VCO) on the basis of different parameters like power dissipation ,phase noise etc. All the design has been done in 45- nm CMOS technology node and 2.3 GHz Centre frequency have been taken for the comparison because of their applications in AV Devices and Radio control. An inherent idea of the given performance parameters has been realize by thecomparative study. The comparative data shows that NMOS based Ring oscillator is good option in terms of the phase noise performance. In this study NMOS Ring Oscillator have attain a phase noise -97.94 dBc/Hz at 1 MHz offset frequency from 2.3 GHz center frequency. The related data also shows that CMOS Ring oscillator is the best option in terms of power consumption. In this work CMOS Ring oscillator evacuatea power of 1.73 mW which is quite low. Keywords: Voltage controlled oscillator (VCO), phase noise, power consumption, Complementary metal-oxide-semiconductor (CMOS), Current Starved Voltage-Controlled Oscillator (CS- VCO), Pull up network (PUN), Pull down network (PDN)

Metal-Dielectric-Graphene Hybrid Heterostructures with Enhanced Surface Plasmon Resonance Sensitivity Based on Amplitude and Phase Measurements

Metal-dielectric-graphene hybrid heterostructures based on oxides Al2O3, HfO2, and ZrO2 as well as on complementary metal–oxide–semiconductor compatible dielectric Si3N4 covering plasmonic metals Cu and Ag have been fabricated and studied. We show that the characteristics of these heterostructures are important for surface plasmon resonance biosensing (such as minimum reflectivity, sharp phase changes, resonance full width at half minimum and resonance sensitivity to refractive index unit (RIU) changes) can be significantly improved by adding dielectric/graphene layers. We demonstrate maximum plasmon resonance spectral sensitivity of more than 30,000 nm/RIU for Cu/Al2O3 (ZrO2, Si3N4), Ag/Si3N4 bilayers and Cu/dielectric/graphene three-layers for near-infrared wavelengths. The sensitivities of the fabricated heterostructures were ~ 5–8 times higher than those of bare Cu or Ag thin films. We also found that the width of the plasmon resonance reflectivity curves can be reduced by adding dielectric/graphene layers. An unexpected blueshift of the plasmon resonance spectral position was observed after covering noble metals with high-index dielectric/graphene heterostructures. We suggest that the observed blueshift and a large enhancement of surface plasmon resonance sensitivity in metal-dielectric-graphene hybrid heterostructures are produced by stationary surface dipoles which generate a strong electric field concentrated at the very thin top dielectric/graphene layer.

Growth of high-quality semiconducting tellurium films for high-performance p-channel field-effect transistors with wafer-scale uniformity

Achieving high-performance p-type semiconductors has been considered one of the most challenging tasks for three-dimensional vertically integrated nanoelectronics. Although many candidates have been presented to date, the facile and scalable realization of high-mobility p-channel field-effect transistors (FETs) is still elusive. Here, we report a high-performance p-channel tellurium (Te) FET fabricated through physical vapor deposition at room temperature. A growth route involving Te deposition by sputtering, oxidation and subsequent reduction to an elemental Te film through alumina encapsulation allows the resulting p-channel FET to exhibit a high field-effect mobility of 30.9 cm2 V−1 s−1 and an ION/OFF ratio of 5.8 × 105 with 4-inch wafer-scale integrity on a SiO2/Si substrate. Complementary metal-oxide semiconductor (CMOS) inverters using In-Ga-Zn-O and 4-nm-thick Te channels show a remarkably high gain of ~75.2 and great noise margins at small supply voltage of 3 V. We believe that this low-cost and high-performance Te layer can pave the way for future CMOS technology enabling monolithic three-dimensional integration.

Spin wave propagation in uniform waveguide: effects, modulation and its application

With the advent of the post-Moore era, researches on beyond-Complementary Metal Oxide Semiconductor (CMOS) approaches have been attracted more and more attention. Magnonics, or spin wave is one of the most promising technology beyond CMOS, which magnons-quanta for spin waves-process the information analogous to electronic charges in electronics. Information transmission by spin waves, which uses the frequency, amplitude and (or) phase to encode information, has a great many of advantages such as extremely low energy loss and wide-band frequency. Moreover, using the nonlinear characteristics of spin waves for information transmission can increase the extra degree of freedom of information. This review provides a tutorial overview over the effects of spin wave propagation and recent research progress in uniform spin wave waveguide. The propagation characteristics of spin waves in uniform waveguides and some special propagation phenomena such as spin wave beam splitting and self-focusing are described by combining experimental phenomena and theoretical formulas. Furthermore, we summarize methods for modulating propagation of spin wave in uniform waveguide, and comment on the advantages and limitations of these methods. The review may promote the development of information transmission technology based on spin waves.

Evaluation of thermal couple impedance model of power modules for accurate die temperature estimation up to 200 ◦C

This paper presents an experimental evaluation of the thermal couple impedance model of power modules (PMs), in which Silicon Carbide (SiC) Metal-Oxide-Semiconductor Field-Effect-Transistor (MOSFET) dies are implemented. The model considers the thermal cross-coupling effect, representing the temperature rise of a die due to power dissipations by the other dies in the same PM. We propose a characterization method to obtain the thermal couple impedance of the SiC MOSFET-based PMs for model accuracy. Simulation based on the proposed model accurately estimates the measured die temperature of three PMs with different die placements. The maximum error between measured and simulated die temperatures is within 8.1 ◦C in a wide and practical operation range from 70 ◦C to 200 ◦C. The thermal couple impedance model is helpful to design die placements of high power PMs considering the thermal cross-coupling effect.

Multipurpose Bio-Monitored Integrated Circuit in a Contact Lens Eye-Tracker

We present the design, fabrication, and test of a multipurpose integrated circuit (Application Specific Integrated Circuit) in AMS 0.35 µm Complementary Metal Oxide Semiconductor technology. This circuit is embedded in a scleral contact lens, combined with photodiodes enabling the gaze direction detection when illuminated and wirelessly powered by an eyewear. The gaze direction is determined by means of a centroid computation from the measured photocurrents. The ASIC is used simultaneously to detect specific eye blinking sequences to validate target designations, for instance. Experimental measurements and validation are performed on a scleral contact lens prototype integrating four infrared photodiodes, mounted on a mock-up eyeball, and combined with an artificial eyelid. The eye-tracker has an accuracy of 0.2°, i.e., 2.5 times better than current mobile video-based eye-trackers, and is robust with respect to process variations, operating time, and supply voltage. Variations of the computed gaze direction transmitted to the eyewear, when the eyelid moves, are detected and can be interpreted as commands based on blink duration or using blinks alternation on both eyes.

In-sensor optoelectronic computing using electrostatically doped silicon

Complementary metal-oxide-semiconductor (CMOS) image sensors are a visual outpost of many machines that interact with the world. While they presently separate image capture in front-end silicon photodiode arrays from image processing in digital back-ends, efforts to process images within the photodiode array itself are rapidly emerging, in hopes of minimizing the data transfer between sensing and computing, and the associated overhead in energy and bandwidth. Electrical modulation, or programming, of photocurrents is requisite for such in-sensor computing, which was indeed demonstrated with electrostatically doped, but non-silicon, photodiodes. CMOS image sensors are currently incapable of in-sensor computing, as their chemically doped photodiodes cannot produce electrically tunable photocurrents. Here we report in-sensor computing with an array of electrostatically doped silicon p-i-n photodiodes, which is amenable to seamless integration with the rest of the CMOS image sensor electronics. This silicon-based approach could more rapidly bring in-sensor computing to the real world due to its compatibility with the mainstream CMOS electronics industry. Our wafer-scale production of thousands of silicon photodiodes using standard fabrication emphasizes this compatibility. We then demonstrate in-sensor processing of optical images using a variety of convolutional filters electrically programmed into a 3 × 3 network of these photodiodes.